CN116725474A - Cornea thickness measuring method and device and computer equipment - Google Patents
Cornea thickness measuring method and device and computer equipment Download PDFInfo
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Abstract
The application discloses a cornea thickness measuring method, a cornea thickness measuring device and computer equipment, which comprise the following steps: acquiring a first Young's model of a cornea to be measured in a first preset direction and a second Young's model of the cornea to be measured in a second preset direction; obtaining a first corner film thickness according to the first Young's model and the second Young's modulus; dividing the cornea to be measured into n subregions; measuring a first surface area, a second surface area and a thickness of the cornea of a corresponding area of each sub-area respectively, wherein the first surface area and the second surface area are areas of different preset surfaces of the sub-areas; obtaining a second cornea thickness according to the first surface area, the second surface area and the thickness respectively corresponding to all the subareas; and obtaining a third cornea thickness according to the first cornea thickness, the second cornea thickness and the pre-acquired cornea influence factor.
Description
Technical Field
The application relates to the technical field of cornea measurement, in particular to a cornea thickness measurement method, a cornea thickness measurement device and computer equipment.
Background
Keratoconus is a keratopathy characterized by a corneal dilation, such that the central portion of the cornea bulges forward, thins into a cone shape and produces a highly irregular astigmatism. The cornea crosslinking technique (CXL) is a new method of treating keratoconus, where an accurate and reproducible measurement of central cornea thickness is particularly important. In the prior art, near infrared low coherence light is irradiated to tissues in the process of measuring the thickness of the cornea, reflected light of a specific level is selectively received and enhanced through an interferometer according to an optical coherence principle, and then back scattered light intensities and delay time of tissues with different depths are obtained, so that cross section imaging and quantitative analysis of shallow biological tissues are realized, and the thickness of the cornea is obtained, but the accuracy of the cornea is still required to be further improved. There is therefore a need to propose a more accurate method of measuring the thickness of the cornea.
Disclosure of Invention
Therefore, in order to solve the defects in the prior art, the embodiment of the application provides a cornea thickness measuring method, a cornea thickness measuring device and computer equipment.
According to a first aspect, an embodiment of the present application discloses a method for measuring a thickness of a cornea, comprising:
acquiring a first Young modulus of a cornea to be measured in a first preset direction and a second Young modulus of the cornea to be measured in a second preset direction;
obtaining a first corner film thickness according to the first Young's model and the second Young's modulus;
dividing the cornea to be measured into n subregions;
measuring a first surface area, a second surface area and a thickness of the cornea of a corresponding area of each sub-area respectively, wherein the first surface area and the second surface area are areas of different preset surfaces of the sub-areas;
obtaining a second cornea thickness according to the first surface area, the second surface area and the thickness respectively corresponding to all the subareas;
and obtaining a third cornea thickness according to the first cornea thickness, the second cornea thickness and the pre-acquired cornea influence factor.
Optionally, obtaining the first thickness of the corner film according to the first young's model and the second young's modulus specifically includes:
inputting the first Young's model and the second Young's modulus into a preset mechanical model to obtain a first thickness of the corner membrane.
Optionally, the first preset direction is an orthogonal direction of the cornea, and the second preset direction is a diagonal direction of the cornea.
Alternatively, the first thickness of the corner film is calculated by the following formula:
D 1 ＝f 1 (E 1 )+f 2 (E 2 )
wherein D is 1 For the first thickness of the corner film E 1 For a first Young's modulus E 2 For a second Young's modulus, f 1 、f 2 Is a preset mechanical model.
Optionally, the cornea influence factor is obtained by:
acquiring characteristic parameters of a cornea to be measured;
and inputting the characteristic parameters into a preset neural network model for training to obtain cornea influence factors.
Alternatively, the second corneal thickness is calculated by the following formula:
wherein D is 2 For a second thickness of the cornea,represents the first surface area of the nth sub-region, < ->A second surface area, d, representing the nth sub-region n Representing the sub-thickness of the cornea of the nth sub-region, S 1 Representing the sum of the first surface areas of the n sub-regions, S 2 Representing the sum of the second surface areas of the n sub-regions.
According to a second aspect, an embodiment of the present application also discloses a cornea thickness measuring apparatus, including:
the first measuring module is used for acquiring a first Young modulus of the cornea to be measured in a first preset direction and a second Young modulus of the cornea to be measured in a second preset direction;
determining a first thickness module, which is used for obtaining a first corner film thickness according to the first Young modulus and the second Young modulus;
the dividing module is used for dividing the cornea to be measured into n subareas;
the second measuring module is used for measuring the first surface area, the second surface area and the thickness of the cornea of the corresponding area of each sub-area respectively, wherein the first surface area and the second surface area are areas of different preset surfaces of the sub-areas;
the second thickness module is used for obtaining a second cornea thickness according to the first surface area, the second surface area and the thickness which are respectively corresponding to all the subareas;
and determining a third thickness module, which is used for obtaining a third cornea thickness according to the first cornea thickness, the second cornea thickness and the pre-acquired cornea influence factor.
Optionally, the first thickness module is determined, specifically for: inputting the first Young modulus and the second Young modulus into a preset mechanical model to obtain a first corner film thickness.
According to a third aspect, an embodiment of the present application further discloses a computer device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform steps of the cornea thickness measurement method as in the first aspect or any of the alternative embodiments of the first aspect.
According to a fourth aspect, an embodiment of the application also discloses a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method for measuring cornea thickness as in the first aspect or any of the alternative embodiments of the first aspect.
The technical scheme of the application has the following advantages:
according to the cornea thickness measuring method, the cornea thickness measuring device and the computer equipment, the first Young modulus of the cornea to be measured in the first preset direction and the second Young modulus of the cornea in the second preset direction are obtained, then the first cornea thickness is determined according to the first Young modulus and the second Young modulus, the Young modulus is measured from the two preset directions in the measuring process, the influence of the arrangement of the cornea stroma collagen fibers in the cornea to be measured on the cornea can be reduced, and therefore the accuracy of the first cornea thickness measurement is ensured; further, dividing the cornea to be measured into n subregions, respectively measuring the first surface area, the second surface area and the thickness of the cornea of the region corresponding to each subregion, obtaining the second cornea thickness of the cornea to be measured according to the first surface area, the second surface area and the thickness of the cornea corresponding to all subregions, dividing the cornea to be measured into n subregions, respectively measuring and determining the second cornea thickness, and more accurately measuring the cornea thickness; and finally, obtaining a third cornea thickness according to the measured first cornea thickness and second cornea thickness and the pre-acquired cornea influence factor.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart showing one specific example of a cornea thickness measuring method according to an embodiment of the present application;
FIG. 2 is a schematic view showing one specific example of a cornea thickness measuring method in the embodiment of the present application;
FIG. 3 is a schematic view showing one specific example of a cornea thickness measuring method in the embodiment of the present application;
FIG. 4 is a schematic view showing one specific example of a cornea thickness measuring method in the embodiment of the present application;
FIG. 5 is a schematic block diagram of a specific example of a cornea thickness measuring apparatus in accordance with an embodiment of the present application;
fig. 6 is a diagram showing a specific example of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the application are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the description of the present application, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; the two components can be directly connected or indirectly connected through an intermediate medium, or can be communicated inside the two components, or can be connected wirelessly or in a wired way. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
In addition, the technical features of the different embodiments of the present application described below may be combined with each other as long as they do not collide with each other.
Keratoconus is a keratopathy characterized by a corneal dilation, such that the central portion of the cornea bulges forward, thins into a cone shape and produces a highly irregular astigmatism. The cornea of the patient is deformed, scared and the corneal oedema in the acute stage can cause the visual acuity to be obviously reduced. The normal cornea has a layer of adhesive fibers (cross-link, composed of keratin sulfate, cartilage sulfate) between its layers of collagen fibers in equilibrium with the corneal tension provided and maintained by the collagen in the corneal tissue, thus allowing the cornea to maintain its normal shape. However, in keratoconus, the material of the adhesive fiber layer between the cornea fiber layers is too small and the supporting property is too weak, and thus the tension in the cornea cannot be resisted. Keratoconus treatment regimens have been revolutionized, once corneal thermoforming, epikeratoplasty (EPK), and few ophthalmic physicians have been developing; the existing mainstream modes include a frame lens, a cornea contact lens, a lens posterior chamber type myopia combined astigmatism artificial lens (TICL) implantation, a stroma ring (intracorneal ringsegments, ICRS) implantation and the like, but the treatment means cannot correct cornea diseases. The cornea crosslinking technology (CXL) is not only a novel method for treating keratoconus, but also a method for correcting myopia. The cornea collagen crosslinking method currently applied in clinic is Ultraviolet/riboflavin cornea crosslinking method (Ultraviolet-A/Riboflavin corneal cross-linking, UV-CXL), which is a method for inducing riboflavin by Ultraviolet irradiation photosensitizerA method for preventing and delaying the progression of keratoconus by improving the biomechanical strength of cornea through crosslinking of collagen fibers in the stroma of the cornea. The cross-linking operation has the meaning that the cross-link is placed into the cornea like a cross beam, so that the cross-link is more stable, and the cross-link can concentrate more force to maintain the shape of the cornea. The standard operation flow is to apply 3mW/cm 2 The ultraviolet light with illumination irradiates the area with diameter of 7-9mm of the center of the cornea infiltrated with riboflavin for 30 minutes so as to achieve the purpose of crosslinking the cornea collagen. Both basic and clinical studies demonstrate that UV-CXL is effective in increasing corneal biomechanical strength. The depth of effect of corneal crosslinking reflects the difference of results of the corneal collagen crosslinking technology, so that an accurate and repeatable central cornea thickness measurement method is particularly important, and the accurate cornea thickness measurement has very important significance and clinical application value in the myopia correction field, and also becomes an urgent need in the ophthalmology field. The cornea thickness also affects whether a patient can perform related cornea refractive surgery, corrects an intraocular pressure value obtained by an applanation tonometry method, monitors the function of endothelium after cornea transplantation, detects cornea thinning problems related to cornea diseases, identifies keratoconus, cornea thinning problems caused by wearing contact lenses and the like. And simultaneously provides visual and reliable reference value for ophthalmic diseases such as ametropia, glaucoma, cataract, presbyopia and the like. Thus, it can be said that the central cornea thickness is not only a physiological and morphological parameter of the eyeball, but also has important pharmacological, diagnostic, pathological and epidemiological significance.
In view of the technical problems mentioned in the background art, an embodiment of the present application provides a method for measuring a thickness of a cornea, specifically referring to fig. 1, the method includes the following steps:
step 101, obtaining a first Young's modulus of the cornea to be measured in a first preset direction and a second Young's modulus of the cornea to be measured in a second preset direction.
For example, when the young's modulus of the cornea to be measured is obtained, the corresponding young's modulus can be determined by a corresponding medical instrument or a relation of strain and stress, wherein young's modulus is a physical quantity describing the deformation resistance of the solid material, that is to say young's modulus is a variable representing the elasticity of the modeling to be measured, whereby the influence of mechanical properties in the cornea to be measured can be represented by young's modulus.
Preferably, considering that the collagen fiber tissue, which is the main component of the cornea, is mainly distributed in the anterior elastic layer and the stroma layer, which are loaded with the main tensile strength of the cornea, wherein the stroma layer occupies 90% of the total thickness and has an elastic modulus greater than that of the other layers, thus being a part mainly loaded, and the collagen fiber of the stroma layer of the cornea is arranged with directionality, thus measuring young's modulus in both the first preset direction and the second preset direction, thereby accurately reflecting the mechanical properties of the cornea.
In a specific embodiment, the first predetermined direction is an orthogonal direction to the cornea and the second predetermined direction is a diagonal direction to the cornea. Wherein the diagonal direction corresponds to the nasal-temporal side of the cornea to be measured (spherical shell cornea) and the orthogonal direction corresponds to the superior-inferior side.
102, obtaining a first corner film thickness according to a first Young modulus and a second Young modulus;
for example, after the first young's modulus and the second young's modulus are measured, a first thickness of the corner film corresponding to the first young's modulus and the second young's modulus can be determined.
In a specific embodiment, the first young's model and the second young's modulus are input to a predetermined mechanical model to obtain the first thickness of the corner film.
The preset mechanical model is as follows: d (D) 1 ＝ 1 (E 1 )+ 2 (E 2 ) Wherein D is 1 For the first thickness of the corner film E 1 For a first Young's modulus E 2 For a second Young's modulus, f 1 、f 2 Is a preset mechanical model.
f 1 、f 2 A nonlinear fitting function can be trained from a large amount of data. Wherein f 1 The training process may be a nonlinear fitting function obtained by training based on the known Young's modulus in the orthogonal direction as an input/output parameter and the Young's modulus in the orthogonal direction as an output. Also f 2 The training process of (2) can be a nonlinear fitting function obtained by training according to the known Young's modulus in the diagonal direction as an input and output parameter and the Young's modulus in the diagonal direction as an output. As shown in fig. 2, in order to obtain a schematic view of the first thickness of the corner, the young's modulus measured in the orthogonal direction is measured in a first predetermined direction to obtain a first young's modulus, the young's modulus measured in the diagonal direction is measured in a second predetermined direction to obtain a second young's modulus, and the first thickness of the corner is obtained through a function (a predetermined mechanical model).
Step 103, dividing the cornea to be measured into n sub-areas.
Step 104, measuring the first surface area, the second surface area and the thickness of the cornea of the corresponding area of each sub-area respectively.
Wherein the first surface area and the second surface area are areas of different preset surfaces of the sub-areas.
Illustratively, the cornea is in a spherical shell shape in the normal physiological state, is stressed in multiple directions, and generates larger errors when the thickness of the cornea is measured by directly adopting an integral measurement method, so that the cornea to be measured is divided into n sub-areas, wherein a specific division process can divide the spherical shell cornea through a limit theory, as shown in fig. 3, whereinFor the cornea on the upper surface area of the first subregion and the upper surface area of the second subregion,/for the cornea>D for the surface area of the cornea under the first subregion and the surface area under the second subregion 1 、d 2 S is the thickness of the cornea in the first subarea and the thickness of the cornea in the second subarea 1 S is the entire upper surface area of the cornea 2 Is the entire lower surface area of the cornea. Dividing the cornea is that n tends to be infinite, and according to the limit theory, the larger n is, the smaller each subregion divided is, and the more accurate the cornea thickness is calculated finally. The upper and lower surface areas and the thickness of each sub-area can be measuredThe measurements were made using a corneal thickness measurement device.
In a specific embodiment, since the cornea is an integral plane, when dividing the cornea into regions, the cornea can be divided according to the LED array to obtain n sub-regions, as shown in fig. 4, which is a schematic diagram of dividing the cornea based on the LED array.
Step 105, obtaining a second cornea thickness according to the first surface area, the second surface area and the thickness respectively corresponding to all the subareas.
Illustratively, after measuring the first surface area, the second surface area, and the thickness for each sub-region, the second corneal thickness may be calculated according to the following equation:
wherein D is 2 For a second thickness of the cornea,represents the first surface area of the nth sub-region, < ->A second surface area, d, representing the nth sub-region n Representing the sub-thickness of the cornea of the nth sub-region, S 1 Representing the sum of the first surface areas of the n sub-regions, S 2 Representing the sum of the second surface areas of the n sub-regions.
And 106, obtaining a third cornea thickness according to the first cornea thickness, the second cornea thickness and the pre-acquired cornea influence factor.
Illustratively, after the first and second corneal thicknesses are obtained, a third corneal thickness is determined from the first and second corneal thicknesses and the pre-acquired corneal impact factor.
Specifically, the third angular membrane thickness can be calculated by the following formula:
wherein D is the thickness of the third membrane; d (D) 1 For the first thickness of the corner film, D 2 Is the second corneal thickness; a1 and A2 are respectively the correlation coefficients of the first cornea thickness and the second cornea thickness, and the correlation coefficients are obtained by statistical analysis fitting of earlier experimental data; k is cornea influencing factor, k ranges from 0 to 2]Preliminary dividing is carried out according to the actual age of the patient of the cornea to be measured, wherein the childhood period k epsilon [ 0-0.7 ]]The period k of middle-aged is 0.8-1.3]The old age period k epsilon is 1.4-2]。
In an alternative embodiment, the cornea influence factor may be further refined by:
acquiring characteristic parameters of a cornea to be measured;
and inputting the characteristic parameters into a preset neural network model for training to obtain cornea influence factors.
By way of example, the characteristic parameters may be parameters of the mean curvature of the cornea, the surface regularity index of the cornea, and the cornea image coefficients, which can be obtained by examining the patient. After the characteristic parameters are obtained, the characteristic parameters can be input into a neural network model for training to obtain cornea influence factors, wherein the specific training process comprises the steps of firstly carrying out data enhancement on the characteristic data through a GAN (generating an countermeasure network Generative Adversarial Network, abbreviated as GAN), then carrying out regression processing according to a LightGBM (Light Gradient Boosting Machine, abbreviated as LightGBM), and finally obtaining the cornea influence factors.
In the above, for the embodiments of the method for measuring the thickness of cornea provided by the present application, the following description describes other embodiments of the method for measuring the thickness of cornea provided by the present application, specifically, see the following.
The embodiment of the application also discloses a cornea thickness measuring device, as shown in fig. 5, which comprises:
a first measurement module 501, configured to obtain a first young's modulus of a cornea to be measured in a first preset direction and a second young's modulus of the cornea to be measured in a second preset direction;
a first thickness determining module 502, configured to obtain a first thickness of the corner film according to the first young's modulus and the second young's modulus;
a dividing module 503, configured to divide the cornea to be measured into n sub-areas;
a second measurement module 504, configured to measure a first surface area, a second surface area, and a thickness of the cornea of the corresponding region of each sub-region, where the first surface area and the second surface area are areas of different preset surfaces of the sub-region;
a second thickness determination module 505, configured to obtain a second cornea thickness according to the first surface area, the second surface area, and the thickness respectively corresponding to all the sub-areas;
a third thickness module 506 is configured to obtain a third corneal thickness based on the first corneal thickness, the second corneal thickness, and the pre-acquired corneal influence factor.
As an alternative embodiment of the present application, the first thickness module is determined, specifically for: inputting the first Young modulus and the second Young modulus into a preset mechanical model to obtain a first corner film thickness.
As an alternative embodiment of the present application, the first preset direction is the orthogonal direction of the cornea, and the second preset direction is the diagonal direction of the cornea.
As an alternative embodiment of the present application, the first thickness of the corner film is calculated by the following formula:
D 1 ＝f 1 (E 1 )+f 2 (E 2 )
wherein D is 1 For the first thickness of the corner film E 1 For a first Young's modulus E 2 For a second Young's modulus, f 1 、f 2 Is a preset mechanical model.
As an alternative embodiment of the present application, the cornea influence factor is obtained by:
acquiring characteristic parameters of a cornea to be measured;
and inputting the characteristic parameters into a preset neural network model for training to obtain cornea influence factors.
As an alternative embodiment of the application, the second corneal thickness is calculated by the following formula:
wherein D is 2 For a second thickness of the cornea,represents the first surface area of the nth sub-region, < ->A second surface area, d, representing the nth sub-region n Representing the sub-thickness of the cornea of the nth sub-region, S 1 Representing the sum of the first surface areas of the n sub-regions, S 2 Representing the sum of the second surface areas of the n sub-regions.
By executing the device, the training targets of the target object are obtained, and the initial training load is determined according to the different training targets of the target object, so that the actual training requirements of the target object can be met; further, according to the relation between the initial training load and the pre-acquired force speed, the ideal training speed of the target object for training under the initial training load in an ideal state is determined, then in the actual training process of the target object, the actual training speed is acquired, and according to the relation between the actual training speed and the ideal training speed, the condition for completing training is determined, so that training according to the actual condition of the target object is realized, and the problem of target object injury caused by unscientific training is avoided.
Embodiments of the present application also provide a computer device, as shown in fig. 6, which may include a processor 601 and a memory 602, where the processor 601 and the memory 602 may be connected by a bus or otherwise, and in fig. 3, the connection is exemplified by a bus.
The processor 601 may be a central processing unit (Central Processing Unit, CPU). The processor 601 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.
The memory 602 serves as a non-transitory computer readable storage medium, and may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the cornea thickness measurement method in the embodiment of the present application. The processor 601 executes various functional applications of the processor and data processing, i.e., implements the cornea thickness measurement method of the above-described method embodiments, by running non-transitory software programs, instructions, and modules stored in the memory 602.
The memory 602 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created by the processor 601, etc. In addition, the memory 602 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 602 may optionally include memory located remotely from processor 601, such remote memory being connectable to processor 601 through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in memory 602 that, when executed by processor 601, perform the cornea thickness measurement method of the embodiment shown in fig. 1.
The details of the above computer device may be understood correspondingly with respect to the corresponding relevant descriptions and effects in the embodiment shown in fig. 1, which are not repeated here.
It will be appreciated by those skilled in the art that implementing all or part of the above-described embodiment method may be implemented by a computer program to instruct related hardware, and the program may be stored in a computer readable storage medium, and the program may include the above-described embodiment method when executed. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present application have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the application, and such modifications and variations are within the scope of the application as defined by the appended claims.
Claims (10)
1. A method of measuring corneal thickness, comprising:
acquiring a first Young modulus of a cornea to be measured in a first preset direction and a second Young modulus of the cornea to be measured in a second preset direction;
obtaining a first corner film thickness according to the first Young's modulus and the second Young's modulus;
dividing the cornea to be measured into n subregions;
measuring a first surface area, a second surface area and a thickness of the cornea of a corresponding area of each subarea respectively, wherein the first surface area and the second surface area are areas of different preset surfaces of the subareas;
obtaining a second cornea thickness according to the first surface area, the second surface area and the thickness respectively corresponding to all the subareas;
and obtaining a third cornea thickness according to the first cornea thickness, the second cornea thickness and the pre-acquired cornea influence factor.
2. The method according to claim 1, wherein the obtaining a first thickness of the corner film according to the first young's modulus and the second young's modulus comprises:
and inputting the first Young's model and the second Young's modulus into a preset mechanical model to obtain the first thickness of the corner membrane.
3. The method of claim 2, wherein the first predetermined direction is an orthogonal direction of the cornea and the second predetermined direction is a diagonal direction of the cornea.
4. A method according to claim 2 or 3, wherein the first thickness of the corner film is calculated by the following formula:
D 1 ＝f 1 (E 1 )+f 2 (E 2 )
wherein D is 1 For the first thickness of the corner film E 1 For a first Young's modulus E 2 For a second Young's modulus, f 1 、f 2 And (5) the model is the preset mechanical model.
5. A method according to any one of claims 1-3, wherein the cornea influencing factor is obtained by:
acquiring characteristic parameters of the cornea to be measured;
and inputting the characteristic parameters into a preset neural network model for training to obtain the cornea influence factor.
6. The method of any one of claims 1-3, wherein the second corneal thickness is calculated by the formula:
wherein D is 2 For a second thickness of the cornea,representing said first surface area of the nth said sub-region,>representing said second surface area, d, of the nth said sub-region n A sub-thickness of the cornea representing the nth of said sub-regions, S 1 Representing the sum of said first surface areas of n sub-regions, S 2 Representing the sum of said second surface areas of the n sub-areas.
7. A corneal thickness measurement device, comprising:
the first measuring module is used for acquiring a first Young modulus of the cornea to be measured in a first preset direction and a second Young modulus of the cornea to be measured in a second preset direction;
a first thickness module is determined and is used for obtaining a first corner film thickness according to the first Young modulus and the second Young modulus;
the dividing module is used for dividing the cornea to be measured into n subareas;
the second measuring module is used for measuring a first surface area, a second surface area and a thickness of the cornea of the area corresponding to each subarea respectively, wherein the first surface area and the second surface area are areas of different preset surfaces of the subareas;
a second thickness module is determined and is used for obtaining a second cornea thickness according to the first surface area, the second surface area and the thickness which are respectively corresponding to all the subareas;
and determining a third thickness module, which is used for obtaining a third thickness of the cornea according to the first thickness of the cornea, the second thickness of the cornea and the pre-acquired cornea influence factor.
8. The apparatus according to claim 7, wherein the determining first thickness module is specifically configured to: and inputting the first Young modulus and the second Young modulus into a preset mechanical model to obtain the first corner film thickness.
9. A computer device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the cornea thickness measurement method of any of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, carries out the steps of the cornea thickness measurement method according to any of claims 1-6.
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| CN202210863733.2A CN116725474A (en) | 2022-07-21 | 2022-07-21 | Cornea thickness measuring method and device and computer equipment |
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| CN202210863733.2A CN116725474A (en) | 2022-07-21 | 2022-07-21 | Cornea thickness measuring method and device and computer equipment |
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